3 papers
cs.CL2026
LLM-based Schema-Guided Extraction and Validation of Missing-Person Intelligence from Heterogeneous Data Sources
Joshua Castillo, Ravi Mukkamala
Missing-person and child-safety investigations rely on heterogeneous case documents, including structured forms, bulletin-style posters, and narrative web profiles. Variations in l…
cs.AI2026
A Consensus-Driven Multi-LLM Pipeline for Missing-Person Investigations
Joshua Castillo, Ravi Mukkamala
The first 72 hours of a missing-person investigation are critical for successful recovery. Guardian is an end-to-end system designed to support missing-child investigation and earl…
cs.AI2026
Interpretable Markov-Based Spatiotemporal Risk Surfaces for Missing-Child Search Planning with Reinforcement Learning and LLM-Based Quality Assurance
Joshua Castillo, Ravi Mukkamala
The first 72 hours of a missing-child investigation are critical for successful recovery. However, law enforcement agencies often face fragmented, unstructured data and a lack of d…